A cyber-attack may employ malware (malicious software), which may include a computer program or file that is harmful to a computer, computer network, and/or user. Conventional antivirus applications may be employed at computers, such as, for example, laptops and servers connectable as nodes (e.g., endpoints) of a network, to identify viruses and other malware using a signature-based approach. Antivirus applications identify malware using an antivirus engine that compares the contents of a file to a database of known malware signatures. Advanced malware often avoids detection by antivirus applications. Advanced malware is often polymorphic in nature, that is, changes its “fingerprint” while maintaining its central malicious functionality, thus avoiding matches against the signature database. Also, advanced malware is often custom-designed for use against targeted users, organizations or industries and not re-used against other targets. As such, targeted malware will often not match signatures of known generic malware. Given that advanced malware is able to circumvent conventional anti-virus analysis, this approach has been determined to be deficient.
Another solution employs a malware detection system to identify malware at the network periphery. In some solutions, detection at the network periphery may utilize a conventional network intrusion detection system (IDS) often incorporated into network firewalls to compare signatures of known malware against traffic for matches while, in other solutions, a two-phase network security appliance (NSA) may be employed. The two-phase approach may compare in-bound network traffic against known characteristics of malware in a static analysis phase and identify malicious behaviors during execution of the content in a dynamic analysis phase.
Detection at the network periphery may be limited by the capability of the malware detection system for precise and effective detection without excessive false positives (wrongly identified attacks) on the one hand (such as is often the case with IDSs), and for timely analysis of behaviors of the network traffic to prevent network intrusion on the other (such as may be the case with some NSAs pending completion of their analysis). Furthermore, the analysis at the network periphery may not provide sufficient information about the particular target or targets (e.g., endpoints) within the network and the potential scope and severity of the attack.
Moreover, the proliferation of malware detection systems and security software has inundated network administrators with security alerts. Actionable intelligence may be buried within these security alerts; however, the sheer number of the alerts makes it difficult for network administrators to identify high priority alerts, a situation exacerbated by the presence of false positives. Moreover, the alerts may not contain sufficient information regarding the progression of the attack once inside the network. Accordingly, a network manager may be unable to identify whether a cyber-attack is in progress or has even occurred and to determine appropriate and timely actions to contain and remediate potential damage.